What are the advantages of using logistic regression?

What are the advantages of using logistic regression?

Logistic regression is great for binary classification problems. It provides probabilities, is easy to interpret, and works well with smaller datasets.

Can you explain why it's easy to interpret?

Sure! The coefficients in logistic regression indicate the change in the log odds of the outcome for a one-unit change in the predictor, making it straightforward to understand the impact of each variable.

Are there any limitations I should be aware of?

Yes, logistic regression assumes a linear relationship between the independent variables and the log odds of the dependent variable, which may not always hold true.

How does it compare to other classification methods?

Compared to methods like decision trees or SVMs, logistic regression is simpler and faster, but it may not capture complex relationships as effectively.

When should I choose logistic regression over other models?

Choose logistic regression when you need a quick, interpretable model for binary outcomes, especially with smaller datasets or when the relationship is approximately linear.